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High frequency millimeter-wave (MMW) radar-like sensors enable the detection of speech signals. This novel non-acoustic speech detection method has some special advantages not offered by traditional microphones, such as preventing strong-acoustic interference, high directional sensitivity with penetration, and long detection distance. A 94-GHz

High frequency millimeter-wave (MMW) radar-like sensors enable the detection of speech signals. This novel non-acoustic speech detection method has some special advantages not offered by traditional microphones, such as preventing strong-acoustic interference, high directional sensitivity with penetration, and long detection distance. A 94-GHz MMW radar sensor was employed in this study to test its speech acquisition ability. A 34-GHz zero intermediate frequency radar, a 34-GHz superheterodyne radar, and a microphone were also used for comparison purposes. A short-time phase-spectrum-compensation algorithm was used to enhance the detected speech. The results reveal that the 94-GHz radar sensor showed the highest sensitivity and obtained the highest speech quality subjective measurement score. This result suggests that the MMW radar sensor has better performance than a traditional microphone in terms of speech detection for detection distances longer than 1 m. As a substitute for the traditional speech acquisition method, this novel speech acquisition method demonstrates a large potential for many speech related applications.
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We explore the use of collocated GPS and seismic sensors for earthquake monitoring and early warning. The GPS and seismic data collected during the 2011 Tohoku-Oki (Japan) and the 2010 El Mayor-Cucapah (Mexico) earthquakes are analyzed by using a tightly-coupled integration. The performance

We explore the use of collocated GPS and seismic sensors for earthquake monitoring and early warning. The GPS and seismic data collected during the 2011 Tohoku-Oki (Japan) and the 2010 El Mayor-Cucapah (Mexico) earthquakes are analyzed by using a tightly-coupled integration. The performance of the integrated results is validated by both time and frequency domain analysis. We detect the P-wave arrival and observe small-scale features of the movement from the integrated results and locate the epicenter. Meanwhile, permanent offsets are extracted from the integrated displacements highly accurately and used for reliable fault slip inversion and magnitude estimation.
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The aim of this work is to develop a microprocessor-based sensor that measures the quality of the offset printing plate through the introduction of different image analysis applications. The main features of the presented system are the low cost, the low amount of

The aim of this work is to develop a microprocessor-based sensor that measures the quality of the offset printing plate through the introduction of different image analysis applications. The main features of the presented system are the low cost, the low amount of power consumption, its modularity and easy integration with other industrial modules for printing plates, and its robustness against noise environments. For the sake of clarity, a viability analysis of previous software is presented through different strategies, based on dynamic histogram and Hough transform. This paper provides performance and scalability data compared with existing costly commercial devices. Furthermore, a general overview of quality control possibilities for printing plates is presented and could be useful to a system where such controls are regularly conducted.
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Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks

Sensor nodes usually have limited energy supply and they are impractical to recharge. How to balance traffic load in sensors in order to increase network lifetime is a very challenging research issue. Many clustering algorithms have been proposed recently for wireless sensor networks (WSNs). However, sensor networks with one fixed sink node often suffer from a hot spots problem since nodes near sinks have more traffic burden to forward during a multi-hop transmission process. The use of mobile sinks has been shown to be an effective technique to enhance network performance features such as latency, energy efficiency, network lifetime, etc. In this paper, a modified Stable Election Protocol (SEP), which employs a mobile sink, has been proposed for WSNs with non-uniform node distribution. The decision of selecting cluster heads by the sink is based on the minimization of the associated additional energy and residual energy at each node. Besides, the cluster head selects the shortest path to reach the sink between the direct approach and the indirect approach with the use of the nearest cluster head. Simulation results demonstrate that our algorithm has better performance than traditional routing algorithms, such as LEACH and SEP.
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The automatic monitoring of shortenings of vertical members in high-rise buildings under construction is a challenging issue in the high-rise building construction field. In this study, a practical system for monitoring column shortening in a high-rise building under construction is presented. The proposed

The automatic monitoring of shortenings of vertical members in high-rise buildings under construction is a challenging issue in the high-rise building construction field. In this study, a practical system for monitoring column shortening in a high-rise building under construction is presented. The proposed monitoring system comprises the following components: (1) a wireless sensing system and (2) the corresponding monitoring software. The wireless sensing system comprises the sensors and energy-efficient wireless sensing units (sensor nodes, master nodes, and repeater nodes), which automate the processes for measuring the strains of vertical members and transmitting the measured data to the remote server. The monitoring software enables construction administrators to monitor real-time data collected by the server via an Internet connection. The proposed monitoring system is applied to actual 66-floor and 72-floor high-rise buildings under construction. The system enables automatic and real-time measurements of the shortening of vertical members, which can result in more precise construction.
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Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All

Finger veins have been proved to be an effective biometric for personal identification in the recent years. However, finger vein images are easily affected by influences such as image translation, orientation, scale, scattering, finger structure, complicated background, uneven illumination, and collection posture. All these factors may contribute to inaccurate region of interest (ROI) definition, and so degrade the performance of finger vein identification system. To improve this problem, in this paper, we propose a finger vein ROI localization method that has high effectiveness and robustness against the above factors. The proposed method consists of a set of steps to localize ROIs accurately, namely segmentation, orientation correction, and ROI detection. Accurate finger region segmentation and correct calculated orientation can support each other to produce higher accuracy in localizing ROIs. Extensive experiments have been performed on the finger vein image database, MMCBNU_6000, to verify the robustness of the proposed method. The proposed method shows the segmentation accuracy of 100%. Furthermore, the average processing time of the proposed method is 22 ms for an acquired image, which satisfies the criterion of a real-time finger vein identification system.
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The present work presents an improved method to align the measurement scale mark in an immersion hydrometer calibration system of CENAM, the National Metrology Institute (NMI) of Mexico, The proposed method uses a vision system to align the scale mark of the hydrometer

The present work presents an improved method to align the measurement scale mark in an immersion hydrometer calibration system of CENAM, the National Metrology Institute (NMI) of Mexico, The proposed method uses a vision system to align the scale mark of the hydrometer to the surface of the liquid where it is immersed by implementing image processing algorithms. This approach reduces the variability in the apparent mass determination during the hydrostatic weighing in the calibration process, therefore decreasing the relative uncertainty of calibration.
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Human action recognition is an increasingly important research topic in the fields of video sensing, analysis and understanding. Caused by unconstrained sensing conditions, there exist large intra-class variations and inter-class ambiguities in realistic videos, which hinder the improvement of recognition performance for recent

Human action recognition is an increasingly important research topic in the fields of video sensing, analysis and understanding. Caused by unconstrained sensing conditions, there exist large intra-class variations and inter-class ambiguities in realistic videos, which hinder the improvement of recognition performance for recent vision-based action recognition systems. In this paper, we propose a generalized pyramid matching kernel (GPMK) for recognizing human actions in realistic videos, based on a multi-channel “bag of words” representation constructed from local spatial-temporal features of video clips. As an extension to the spatial-temporal pyramid matching (STPM) kernel, the GPMK leverages heterogeneous visual cues in multiple feature descriptor types and spatial-temporal grid granularity levels, to build a valid similarity metric between two video clips for kernel-based classification. Instead of the predefined and fixed weights used in STPM, we present a simple, yet effective, method to compute adaptive channel weights of GPMK based on the kernel target alignment from training data. It incorporates prior knowledge and the data-driven information of different channels in a principled way. The experimental results on three challenging video datasets (i.e., Hollywood2, Youtube and HMDB51) validate the superiority of our GPMK w.r.t. the traditional STPM kernel for realistic human action recognition and outperform the state-of-the-art results in the literature.
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In this study, we focused on microfluidic electrochemical analysis of zinc complexes (Zn(phen)(his)Cl2, Zn(his)Cl2) and ZnS quantum dots (QDs) using printed electrodes. This method was chosen due to the simple (easy to use) instrumentation and variable setting of flows.

In this study, we focused on microfluidic electrochemical analysis of zinc complexes (Zn(phen)(his)Cl2, Zn(his)Cl2) and ZnS quantum dots (QDs) using printed electrodes. This method was chosen due to the simple (easy to use) instrumentation and variable setting of flows. Reduction signals of zinc under the strictly defined and controlled conditions (pH, temperature, flow rate, accumulation time and applied potential) were studied. We showed that the increasing concentration of the complexes (Zn(phen)(his)Cl2, Zn(his)Cl2) led to a decrease in the electrochemical signal and a significant shift of the potential to more positive values. The most likely explanation of this result is that zinc is strongly bound in the complex and its distribution on the electrode is very limited. Changing the pH from 3.5 to 5.5 resulted in a significant intensification of the Zn(II) reduction signal. The complexes were also characterized by UV/VIS spectrophotometry, chromatography, and ESI-QTOF mass spectrometry.
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Improving efficiency of city services and facilitating a more sustainable development of cities are the main drivers of the smart city concept. Information and Communication Technologies (ICT) play a crucial role in making cities smarter, more accessible and more open. In this paper

Improving efficiency of city services and facilitating a more sustainable development of cities are the main drivers of the smart city concept. Information and Communication Technologies (ICT) play a crucial role in making cities smarter, more accessible and more open. In this paper we present a novel architecture exploiting major concepts from the Future Internet (FI) paradigm addressing the challenges that need to be overcome when creating smarter cities. This architecture takes advantage of both the critical communications infrastructures already in place and owned by the utilities as well as of the infrastructure belonging to the city municipalities to accelerate efficient provision of existing and new city services. The paper highlights how FI technologies create the necessary glue and logic that allows the integration of current vertical and isolated city services into a holistic solution, which enables a huge forward leap for the efficiency and sustainability of our cities. Moreover, the paper describes a real-world prototype, that instantiates the aforementioned architecture, deployed in one of the parks of the city of Santander providing an autonomous public street lighting adaptation service. This prototype is a showcase on how added-value services can be seamlessly created on top of the proposed architecture.
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This paper presents the implementation of power fluctuation compensation for an intensity-based optical fibre bending sensor aimed at monitoring human spine bending in a clinical environment. To compensate for the light intensity changes from the sensor light source, a reference signal was provided

This paper presents the implementation of power fluctuation compensation for an intensity-based optical fibre bending sensor aimed at monitoring human spine bending in a clinical environment. To compensate for the light intensity changes from the sensor light source, a reference signal was provided via the light reflection from an aluminum foil surface fixed at a certain distance from the source fibre end tips. From the results, it was found that the investigated sensor compensation technique was capable of achieving a 2° resolution for a bending angle working range between 0° and 20°. The study also suggested that the output voltage ratio has a 0.55% diversion due to input voltage variation between 2.9 V and 3.4 V and a 0.25% output drift for a 2 h measurement. With the achieved sensor properties, human spine monitoring in a clinical environment can potentially be implemented using this approach with power fluctuation compensation.
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This paper presents a new segmentation-based algorithm for oil spill feature extraction from Synthetic Aperture Radar (SAR) intensity images. The proposed algorithm combines a Voronoi tessellation, Bayesian inference and Markov Chain Monte Carlo (MCMC) scheme. The shape and distribution features of dark spots can be obtained by segmenting a scene covering an oil spill and/or look-alikes into two homogenous regions: dark spots and their marine surroundings. The proposed algorithm is applied simultaneously to several real SAR intensity images and simulated SAR intensity images which are used for accurate evaluation. The results show that the proposed algorithm can extract the shape and distribution parameters of dark spot areas, which are useful for recognizing oil spills in a further classification stage.
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In this study, we introduce a wide spectral range (200–2500 nm) imaging system with a 250 μm minimum spatial resolution, which can be freely modified for a wide range of resolutions and measurement geometries. The system has been tested for reflectance and luminescence

In this study, we introduce a wide spectral range (200–2500 nm) imaging system with a 250 μm minimum spatial resolution, which can be freely modified for a wide range of resolutions and measurement geometries. The system has been tested for reflectance and luminescence measurements, but can also be customized for transmittance measurements. This study includes the performance results of the developed system, as well as examples of spectral images. Discussion of the system relates it to existing systems and methods. The wide range spectral imaging system that has been developed is however highly customizable and has great potential in many practical applications.
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We report on the spatial and temporal signaling properties of a yeast pheromone-based cell communication and amplifier system. It utilizes the Saccharomyces cerevisiae mating response pathway and relies on diffusion of the pheromone α–factor as key signaling molecule between two cell types. One

We report on the spatial and temporal signaling properties of a yeast pheromone-based cell communication and amplifier system. It utilizes the Saccharomyces cerevisiae mating response pathway and relies on diffusion of the pheromone α–factor as key signaling molecule between two cell types. One cell type represents the α–factor secreting sensor part and the other the reporter part emitting fluorescence upon activation. Although multi-cellular signaling systems promise higher specificity and modularity, the complex interaction of the cells makes prediction of sensor performance difficult. To test the maximum distance and response time between sensor and reporter cells, the two cell types were spatially separated in defined compartments of agarose hydrogel (5 ´ 5 mm) and reconnected by diffusion of the yeast pheromone. Different ratios of sensor to reporter cells were tested to evaluate the minimum amount of sensor cells required for signal transduction. Even the smallest ratio, one α–factor-secreting cell to twenty reporter cells, generated a distinct fluorescence signal. When using a 1:1 ratio, the secreted pheromone induced fluorescence in a distance of up to four millimeters after six hours. We conclude from both our experimental results and a mathematical diffusion model that in our approach: (1) the maximum dimension of separated compartments should not exceed five millimeters in gradient direction; and (2) the time-limiting step is not diffusion of the signaling molecule but production of the reporter protein.
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A broad range hyper-spectroscopic microscope fed by a supercontinuum laser source and equipped with an almost achromatic optical layout is illustrated with detailed explanations of the design, implementation and data. The real novelty of this instrument, a confocal spectroscopic microscope capable of recording

A broad range hyper-spectroscopic microscope fed by a supercontinuum laser source and equipped with an almost achromatic optical layout is illustrated with detailed explanations of the design, implementation and data. The real novelty of this instrument, a confocal spectroscopic microscope capable of recording high resolution reflectance data in the VIS-IR spectral range from about 500 nm to 2.5 μm wavelengths, is the possibility of acquiring spectral data at every physical point as defined by lateral coordinates, X and Y, as well as at a depth coordinate, Z, as obtained by the confocal optical sectioning advantage. With this apparatus we collect each single scanning point as a whole spectrum by combining two linear spectral detector arrays, one CCD for the visible range, and one InGaAs infrared array, simultaneously available at the sensor output channel of the home made instrument. This microscope has been developed for biomedical analysis of human skin and other similar applications. Results are shown illustrating the technical performances of the instrument and the capability in extracting information about the composition and the structure of different parts or compartments in biological samples as well as in solid statematter. A complete spectroscopic fingerprinting of samples at microscopic level is shown possible by using statistical analysis on raw data or analytical reflectance models based on Abelés matrix transfer methods.
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As a “chemical antibody”, oligonucleotide aptamers can specifically bind to their target molecules. However, clinical potential of aptamers in disease diagnosis is not yet fully explored. Using a tumor cell-based selection protocol, we developed single-stranded DNA aptamers for Hodgkin lymphoma (HL) tumor cells.

As a “chemical antibody”, oligonucleotide aptamers can specifically bind to their target molecules. However, clinical potential of aptamers in disease diagnosis is not yet fully explored. Using a tumor cell-based selection protocol, we developed single-stranded DNA aptamers for Hodgkin lymphoma (HL) tumor cells. The aptamers specifically bound to HL cells with a high affinity, reaching maximal cell binding at 10 nM final concentration. Importantly, the aptamers were able to selectively detect HL cells and did not react to other tumor or blood cells in mixed samples, indicating that the aptamers can be used as a specific probe for in vitro analysis of HL cells. Moreover, due to the inherent properties of DNA, the aptamers were stable in human serum, suggesting potential for in vivo detection of HL tumor cells.
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The discovery of quorum sensing in Proteobacteria and its function in regulating virulence determinants makes it an attractive alternative towards attenuation of bacterial pathogens. In this study, crude extracts of Phyllanthus amarus Schumach. & Thonn, a traditional Chinese herb, were screened for their

The discovery of quorum sensing in Proteobacteria and its function in regulating virulence determinants makes it an attractive alternative towards attenuation of bacterial pathogens. In this study, crude extracts of Phyllanthus amarus Schumach. & Thonn, a traditional Chinese herb, were screened for their anti-quorum sensing properties through a series of bioassays. Only the methanolic extract of P. amarus exhibited anti-quorum sensing activity, whereby it interrupted the ability of Chromobacterium violaceum CVO26 to response towards exogenously supplied N-hexanoylhomoserine lactone and the extract reduced bioluminescence in E. coli [pSB401] and E. coli [pSB1075]. In addition to this, methanolic extract of P. amarus significantly inhibited selected quorum sensing-regulated virulence determinants of Pseudomonas aeruginosa PA01. Increasing concentrations of the methanolic extracts of P. amarus reduced swarming motility, pyocyanin production and P. aeruginosa PA01 lecA::lux expression. Our data suggest that P. amarus could be useful for attenuating pathogens and hence, more local traditional herbs should be screened for its anti-quorum sensing properties as their active compounds may serve as promising anti-pathogenic drugs.
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Mood disorders are common mental diseases, but physiological diagnostic methods are still lacking. Since much evidence has implied a relationship between mood disorders and the protein composition of blood sera, it is conceivable to develop a serological criterion for assisting diagnosis of mood

Mood disorders are common mental diseases, but physiological diagnostic methods are still lacking. Since much evidence has implied a relationship between mood disorders and the protein composition of blood sera, it is conceivable to develop a serological criterion for assisting diagnosis of mood disorders, based on a correlative database with enough capacity and high quality. In this pilot study, a low-cost microfluidic microarray device for quantifying at most 384 serological biomarkers at the same time was designed for the data acquisition of the serological study. The 1,536-chamber microfluidic device was modeled on a 1,536-well microtiter plate in order to employ a common microplate reader as the detection module for measuring the chemiluminescent immunoassay tests on the chips. The microfluidic microarrays were rapidly fabricated on polymethylmethacrylate slides using carbon dioxide laser ablation, followed by effective surface treatment processing. Sixteen types of different capture antibodies were immobilized on the chips to test the corresponding hormones and cytokines. The preliminary tests indicated that the signal-to-noise ratio and the limit of detection of microfluidic microarrays have reached the level of standard ELISA tests, whereas the operation time of microfluidic microarrays was sharply reduced.
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Since the drifts of Inertial Navigation System (INS) solutions are inevitable and also grow over time, a Doppler Velocity Log (DVL) is used to aid the INS to restrain its error growth. Therefore, INS/DVL integration is a common approach for Autonomous Underwater Vehicle

Since the drifts of Inertial Navigation System (INS) solutions are inevitable and also grow over time, a Doppler Velocity Log (DVL) is used to aid the INS to restrain its error growth. Therefore, INS/DVL integration is a common approach for Autonomous Underwater Vehicle (AUV) navigation. The parameters including the scale factor of DVL and misalignments between INS and DVL are key factors which limit the accuracy of the INS/DVL integration. In this paper, a novel parameter calibration method is proposed. An iterative implementation of the method is designed to reduce the error caused by INS initial alignment. Furthermore, a simplified INS/DVL integration scheme is employed. The proposed method is evaluated with both river trial and sea trial data sets. Using 0.03°/h(1σ) ring laser gyroscopes, 5 × 10−5 g(1σ) quartz accelerometers and DVL with accuracy 0.5% V ± 0.5 cm/s, INS/DVL integrated navigation can reach an accuracy of about 1‰ of distance travelled (CEP) in a river trial and 2‰ of distance travelled (CEP) in a sea trial.
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We investigate a highly sensitive optical sensor based on two cascaded microring resonators exploiting the Vernier effect. The architecture consists of two microrings with a slight difference in their free spectral ranges. This allows the generation of the Vernier effect for achieving ultra-high

We investigate a highly sensitive optical sensor based on two cascaded microring resonators exploiting the Vernier effect. The architecture consists of two microrings with a slight difference in their free spectral ranges. This allows the generation of the Vernier effect for achieving ultra-high sensitivities. The sensor chip was fabricated using a silicon nitride platform and characterized with isopropanol/ethanol mixtures. A sensitivity of 0.95 nm/% was found for isopropanol concentrations in ethanol ranging from 0% to 10%. Furthermore, a collection of measurements was carried out using aqueous sodium chloride (NaCl) in solutions of different concentrations, confirming a high sensitivity of 10.3 nm/% and a bulk refractive index sensitivity of 6,317 nm/RIU. A limit of detection of 3.16 ´ 10−6 RIU was determined. These preliminary results show the potential features of cascaded silicon nitride microring resonators for real-time and free-label monitoring of biomolecules for a broad range of applications.
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Recent developments in hardware and software have increased the possibilities and reduced the costs of hyperspectral proximal sensing. Through the analysis of high resolution spectroscopic measurements at the laboratory or field scales, this monitoring technique is suitable for quantitative estimates of biochemical and

Recent developments in hardware and software have increased the possibilities and reduced the costs of hyperspectral proximal sensing. Through the analysis of high resolution spectroscopic measurements at the laboratory or field scales, this monitoring technique is suitable for quantitative estimates of biochemical and biophysical variables related to the physiological state of vegetation. Two systems for hyperspectral imaging have been designed and developed at DICEA-Sapienza University of Rome, one based on the use of spectrometers, the other on tunable interference filters. Both systems provide a high spectral and spatial resolution with low weight, power consumption and cost. This paper describes the set-up of the tunable filter platform and its application to the investigation of the environmental status of the region crossed by the Sacco river (Latium, Italy). This was achieved by analyzing the spectral response given by tree samples, with roots partly or wholly submerged in the river, located upstream and downstream of an industrial area affected by contamination. Data acquired is represented as reflectance indices as well as reflectance values. Broadband and narrowband indices based on pigment content and carotenoids vs. chlorophyll content suggest tree samples located upstream of the contaminated area are ‘healthier’ than those downstream.
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In this article we describe the integration of impedance spectroscopy (EIS) and surface plasmon resonance (SPR) into one surface analytic device. A polydimethylsiloxane (PDMS) flow cell is created, matching the dimensions of a commercially available sensor chip used for SPR measurements. This flow

In this article we describe the integration of impedance spectroscopy (EIS) and surface plasmon resonance (SPR) into one surface analytic device. A polydimethylsiloxane (PDMS) flow cell is created, matching the dimensions of a commercially available sensor chip used for SPR measurements. This flow cell allowed simultaneous measurements between an EIS and a SPR setup. After a successful integration, a proof of principle study was conducted to investigate any signs of interference between the two systems during a measurement. The flow cell was rinsed with 10 mM Tris-HCl and 1× PBS buffer in an alternating manner, while impedance and shifts of the resonance angle were monitored. After achieving a successful proof of principle, a usability test was conducted. It was assessed whether simultaneous detection occurred when: (i) Protein A is adsorbed to the gold surface of the chip; (ii) The non-occupied zone is blocked with BSA molecules and (iii) IgG1 is bound to the Protein A. The results indicate a successful merge between SPR and EIS.
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In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.
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In this paper a refractive index sensor based on localized surface plasmon resonance (LSPR) in a Plastic Optical Fiber (POF), is presented and experimentally tested. LSPR is achieved exploiting five-branched gold nanostars (GNS) obtained using Triton X-100 in a seed-growth synthesis. They have

In this paper a refractive index sensor based on localized surface plasmon resonance (LSPR) in a Plastic Optical Fiber (POF), is presented and experimentally tested. LSPR is achieved exploiting five-branched gold nanostars (GNS) obtained using Triton X-100 in a seed-growth synthesis. They have the uncommon feature of three localized surface plasmon resonances. The strongest LSPRs fall in two ranges, one in the 600–900 nm range (LSPR 2) and the other one in the 1,100–1,600 nm range (LSPR 3), both sensible to refractive index changes. Anyway, due to the extremely strong attenuation (>102 dB/m) of the employed POF in the 1,100–1,600 nm range, only LSPR 2 will be exploited for refractive index change measurements, useful for bio-chemical sensing applications, as a proof of principle of the possibility of realizing a compact, low cost and easy-to-use GNS based device.
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Detecting people is a key capability for robots that operate in populated environments. In this paper, we have adopted a hierarchical approach that combines classifiers created using supervised learning in order to identify whether a person is in the view-scope of the robot

Detecting people is a key capability for robots that operate in populated environments. In this paper, we have adopted a hierarchical approach that combines classifiers created using supervised learning in order to identify whether a person is in the view-scope of the robot or not. Our approach makes use of vision, depth and thermal sensors mounted on top of a mobile platform. The set of sensors is set up combining the rich data source offered by a Kinect sensor, which provides vision and depth at low cost, and a thermopile array sensor. Experimental results carried out with a mobile platform in a manufacturing shop floor and in a science museum have shown that the false positive rate achieved using any single cue is drastically reduced. The performance of our algorithm improves other well-known approaches, such as C4 and histogram of oriented gradients (HOG).
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A microfluidic bioreactor with an easy to fabricate nano-plasmonic surface is demonstrated for studies of biofilms and their precursor materials via Surface Enhanced Raman Spectroscopy (SERS). The system uses a novel design to induce sheath flow confinement of a sodium citrate biofilm precursor

A microfluidic bioreactor with an easy to fabricate nano-plasmonic surface is demonstrated for studies of biofilms and their precursor materials via Surface Enhanced Raman Spectroscopy (SERS). The system uses a novel design to induce sheath flow confinement of a sodium citrate biofilm precursor stream against the SERS imaging surface to measure spatial variations in the concentration profile. The unoptimised SERS enhancement was approximately 2.5 × 104, thereby improving data acquisition time, reducing laser power requirements and enabling a citrate detection limit of 0.1 mM, which was well below the concentrations used in biofilm nutrient solutions. The flow confinement was observed by both optical microscopy and SERS imaging with good complementarity. We demonstrate the new bioreactor by growing flow-templated biofilms on the microchannel wall. This work opens the way for in situ spectral imaging of biofilms and their biochemical environment under dynamic flow conditions.
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This study investigates the design and fabrication of magnetic microsensors using the commercial 0.35 μm complementary metal oxide semiconductor (CMOS) process. The magnetic sensor is composed of springs and interdigitated electrodes, and it is actuated by the Lorentz force. The finite element method

This study investigates the design and fabrication of magnetic microsensors using the commercial 0.35 μm complementary metal oxide semiconductor (CMOS) process. The magnetic sensor is composed of springs and interdigitated electrodes, and it is actuated by the Lorentz force. The finite element method (FEM) software CoventorWare is adopted to simulate the displacement and capacitance of the magnetic sensor. A post-CMOS process is utilized to release the suspended structure. The post-process uses an anisotropic dry etching to etch the silicon dioxide layer and an isotropic dry etching to remove the silicon substrate. When a magnetic field is applied to the magnetic sensor, it generates a change in capacitance. A sensing circuit is employed to convert the capacitance variation of the sensor into the output voltage. The experimental results show that the output voltage of the magnetic microsensor varies from 0.05 to 1.94 V in the magnetic field range of 5–200 mT.
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Field measurements of the swimming activity rhythms of fishes are scant due to the difficulty of counting individuals at a high frequency over a long period of time. Cabled observatory video monitoring allows such a sampling at a high frequency over unlimited periods

Field measurements of the swimming activity rhythms of fishes are scant due to the difficulty of counting individuals at a high frequency over a long period of time. Cabled observatory video monitoring allows such a sampling at a high frequency over unlimited periods of time. Unfortunately, automation for the extraction of biological information (i.e., animals’ visual counts per unit of time) is still a major bottleneck. In this study, we describe a new automated video-imaging protocol for the 24-h continuous counting of fishes in colorimetrically calibrated time-lapse photographic outputs, taken by a shallow water (20 m depth) cabled video-platform, the OBSEA. The spectral reflectance value for each patch was measured between 400 to 700 nm and then converted into standard RGB, used as a reference for all subsequent calibrations. All the images were acquired within a standardized Region Of Interest (ROI), represented by a 2 × 2 m methacrylate panel, endowed with a 9-colour calibration chart, and calibrated using the recently implemented “3D Thin-Plate Spline” warping approach in order to numerically define color by its coordinates in n-dimensional space. That operation was repeated on a subset of images, 500 images as a training set, manually selected since acquired under optimum visibility conditions. All images plus those for the training set were ordered together through Principal Component Analysis allowing the selection of 614 images (67.6%) out of 908 as a total corresponding to 18 days (at 30 min frequency). The Roberts operator (used in image processing and computer vision for edge detection) was used to highlights regions of high spatial colour gradient corresponding to fishes’ bodies. Time series in manual and visual counts were compared together for efficiency evaluation. Periodogram and waveform analysis outputs provided very similar results, although quantified parameters in relation to the strength of respective rhythms were different. Results indicate that automation efficiency is limited by optimum visibility conditions. Data sets from manual counting present the larger day-night fluctuations in comparison to those derived from automation. This comparison indicates that the automation protocol subestimate fish numbers but it is anyway suitable for the study of community activity rhythms.
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Purpose: To compare raw acceleration output of the ActiGraph™ GT3X+ and GENEA activity monitors. Methods: A GT3X+ and GENEA were oscillated in an orbital shaker at frequencies ranging from 0.7 to 4.0 Hz (ten 2-min trials/frequency) on a fixed radius of

Purpose: To compare raw acceleration output of the ActiGraph™ GT3X+ and GENEA activity monitors. Methods: A GT3X+ and GENEA were oscillated in an orbital shaker at frequencies ranging from 0.7 to 4.0 Hz (ten 2-min trials/frequency) on a fixed radius of 5.08 cm. Additionally, 10 participants (age = 23.8 ± 5.4 years) wore the GT3X+ and GENEA on the dominant wrist and performed treadmill walking (2.0 and 3.5 mph) and running (5.5 and 7.5 mph) and simulated free-living activities (computer work, cleaning a room, vacuuming and throwing a ball) for 2-min each. A linear mixed model was used to compare the mean triaxial vector magnitude (VM) from the GT3X+ and GENEA at each oscillation frequency. For the human testing protocol, random forest machine-learning technique was used to develop two models using frequency domain (FD) and time domain (TD) features for each monitor. We compared activity type recognition accuracy between the GT3X+ and GENEA when the prediction model was fit using one monitor and then applied to the other. Z-statistics were used to compare the proportion of accurate predictions from the GT3X+ and GENEA for each model. Results:GENEA produced significantly higher (p < 0.05, 3.5 to 6.2%) mean VM than GT3X+ at all frequencies during shaker testing. Training the model using TD input features on the GENEA and applied to GT3X+ data yielded significantly lower (p < 0.05) prediction accuracy. Prediction accuracy was not compromised when interchangeably using FD models between monitors. Conclusions: It may be inappropriate to apply a model developed on the GENEA to predict activity type using GT3X+ data when input features are TD attributes of raw acceleration.
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The detection of partial discharge and analysis of SF6 gas components in gas-insulated switchgear (GIS) is important for the diagnosis and operating state assessment of power equipment. The use of a Pt-doped TiO2 nanotube arrays sensor for detecting sulfur hexafluoride (SF

The detection of partial discharge and analysis of SF6 gas components in gas-insulated switchgear (GIS) is important for the diagnosis and operating state assessment of power equipment. The use of a Pt-doped TiO2 nanotube arrays sensor for detecting sulfur hexafluoride (SF6) decomposition products is proposed in this paper. The electrochemical pulse deposition method is employed to prepare the sensor array. The sensor’s response to the main characteristic gaseous decomposition products of SF6 is evaluated. The gas sensing characteristic curves of the Pt-doped TiO2 nanotube sensor and intrinsic TiO2 nanotube arrays sensor are compared. The mechanism of the sensitive response is discussed. Test results showed that the Pt-doped nanoparticles not only change the gas sensing selectivity of the TiO2 nanotube arrays sensor with respect to the main characteristic SF6 decomposition products, but also reduce the operating temperature of the sensor.
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In this work, deionized (DI) water dissociation was used to treat and change the contact angle of the surface of stainless steel substrates followed by the spin coating of P(VDF-TrFE) material for the fabrication of tactile sensors. The contact angle of the stainless

In this work, deionized (DI) water dissociation was used to treat and change the contact angle of the surface of stainless steel substrates followed by the spin coating of P(VDF-TrFE) material for the fabrication of tactile sensors. The contact angle of the stainless steel surface decreased 14° at −30 V treatment; thus, the adhesion strength between the P(VDF-TrFE) thin film and the stainless steel substrate increased by 90%. Although the adhesion strength was increased at negative voltage treatment, it is observed that the crystallinity value of the P(VDF-TrFE) thin film declined to 37% at −60 V. In addition, the remanent polarization value of the P(VDF-TrFE) thin film declined from 5.6 mC/cm2 to 4.61 mC/cm2 for treatment voltages between −5 V and −60 V. A maximum value of approximately 1000 KV/cm of the coercive field value was obtained with the treatment at −15 V. The d33 value was approximately −10.7 pC/N for the substrate treated at 0 V and reached a minimum of −5 pC/N for treatment at −60 V. By using the P(VDF-TrFE) thin-film as the sensing material for tactile sensors, human pulse measurements were obtained from areas including the carotid, brachial, ankle, radial artery, and apical regions. In addition, the tactile sensor is suitable for monitoring the Cun, Guan, and Chi acupoints located at the radial artery region in Traditional Chinese Medicine (TCM). Waveform measurements of the Cun, Guan, and Chi acupoints are crucial because, in TCM, the various waveforms provided information regarding the health conditions of organs.
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In the current study, a non-invasive technique for systolic blood pressure (SBP) measurement based on the detection of photoplethysmographic (PPG) pulses during pressure-cuff deflation was compared to sphygmomanometry—the Korotkoff sounds technique. The PPG pulses disappear for cuff-pressures above the SBP value and reappear

In the current study, a non-invasive technique for systolic blood pressure (SBP) measurement based on the detection of photoplethysmographic (PPG) pulses during pressure-cuff deflation was compared to sphygmomanometry—the Korotkoff sounds technique. The PPG pulses disappear for cuff-pressures above the SBP value and reappear when the cuff-pressure decreases below the SBP value. One hundred and twenty examinations were performed on forty subjects. In 97 examinations the two methods differed by less than 3 mmHg. In nine examinations the SBP value measured by PPG was higher than that measured by sphygmomanometry by 5 mmHg or more. In only one examination the former was lower by 5 mmHg or more than the latter. The appearance of either the PPG pulses or the Korotkoff sounds assures that the artery under the cuff is open during systolic peak pressure. In the nine examinations mentioned above the PPG pulses were observed while Korotkoff sounds were not detected, despite the open artery during systole. In these examinations, the PPG-based technique was more reliable than sphygmomanometry. The high signal-to-noise ratio of measured PPG pulses indicates that automatic measurement of the SBP by means of automatic detection of the PPG signals is feasible.
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Ocular contamination of EEG data is an important and very common problem in the diagnosis of neurobiological events. An effective approach is proposed in this paper to remove ocular artifacts from the raw EEG recording. First, it conducts the blind source separation on

Ocular contamination of EEG data is an important and very common problem in the diagnosis of neurobiological events. An effective approach is proposed in this paper to remove ocular artifacts from the raw EEG recording. First, it conducts the blind source separation on the raw EEG recording by the stationary subspace analysis, which can concentrate artifacts in fewer components than the representative blind source separation methods. Next, to recover the neural information that has leaked into the artifactual components, the adaptive signal decomposition technique EMD is applied to denoise the components. Finally, the artifact-only components are projected back to be subtracted from EEG signals to get the clean EEG data. The experimental results on both the artificially contaminated EEG data and publicly available real EEG data have demonstrated the effectiveness of the proposed method, in particular for the cases where limited number of electrodes are used for the recording, as well as when the artifact contaminated signal is highly non-stationary and the underlying sources cannot be assumed to be independent or uncorrelated.
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This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA) and fuzzy C-means (FCM) algorithm are used for feature extraction and clustering, respectively.

This paper presents a novel hardware architecture for fast spike sorting. The architecture is able to perform both the feature extraction and clustering in hardware. The generalized Hebbian algorithm (GHA) and fuzzy C-means (FCM) algorithm are used for feature extraction and clustering, respectively. The employment of GHA allows efficient computation of principal components for subsequent clustering operations. The FCM is able to achieve near optimal clustering for spike sorting. Its performance is insensitive to the selection of initial cluster centers. The hardware implementations of GHA and FCM feature low area costs and high throughput. In the GHA architecture, the computation of different weight vectors share the same circuit for lowering the area costs. Moreover, in the FCM hardware implementation, the usual iterative operations for updating the membership matrix and cluster centroid are merged into one single updating process to evade the large storage requirement. To show the effectiveness of the circuit, the proposed architecture is physically implemented by field programmable gate array (FPGA). It is embedded in a System-on-Chip (SOC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient spike sorting design for attaining high classification correct rate and high speed computation.
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Internet of Things (IoT) networks are the pillar of recent novel scenarios, such as smart cities or e-healthcare applications. Among other challenges, these networks cover the deployment and interaction of small devices with constrained capabilities and Internet protocol (IP)-based networking connectivity. These constrained

Internet of Things (IoT) networks are the pillar of recent novel scenarios, such as smart cities or e-healthcare applications. Among other challenges, these networks cover the deployment and interaction of small devices with constrained capabilities and Internet protocol (IP)-based networking connectivity. These constrained devices usually require connection to the Internet to exchange information (e.g., management or sensing data) or access network services. However, only authenticated and authorized devices can, in general, establish this connection. The so-called authentication, authorization and accounting (AAA) services are in charge of performing these tasks on the Internet. Thus, it is necessary to deploy protocols that allow constrained devices to verify their credentials against AAA infrastructures. The Protocol for Carrying Authentication for Network Access (PANA) has been standardized by the Internet engineering task force (IETF) to carry the Extensible Authentication Protocol (EAP), which provides flexible authentication upon the presence of AAA. To the best of our knowledge, this paper is the first deep study of the feasibility of EAP/PANA for network access control in constrained devices. We provide light-weight versions and implementations of these protocols to fit them into constrained devices. These versions have been designed to reduce the impact in standard specifications. The goal of this work is two-fold: (1) to demonstrate the feasibility of EAP/PANA in IoT devices; (2) to provide the scientific community with the first light-weight interoperable implementation of EAP/PANA for constrained devices in the Contiki operating system (Contiki OS), called PANATIKI. The paper also shows a testbed, simulations and experimental results obtained from real and simulated constrained devices.
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This paper deals with the problem of humanoid robot localization and proposes a new method for position estimation that has been developed for the RoboCup Standard Platform League environment. Firstly, a complete vision system has been implemented in the Nao robot platform that

This paper deals with the problem of humanoid robot localization and proposes a new method for position estimation that has been developed for the RoboCup Standard Platform League environment. Firstly, a complete vision system has been implemented in the Nao robot platform that enables the detection of relevant field markers. The detection of field markers provides some estimation of distances for the current robot position. To reduce errors in these distance measurements, extrinsic and intrinsic camera calibration procedures have been developed and described. To validate the localization algorithm, experiments covering many of the typical situations that arise during RoboCup games have been developed: ranging from degradation in position estimation to total loss of position (due to falls, ‘kidnapped robot’, or penalization). The self-localization method developed is based on the classical particle filter algorithm. The main contribution of this work is a new particle selection strategy. Our approach reduces the CPU computing time required for each iteration and so eases the limited resource availability problem that is common in robot platforms such as Nao. The experimental results show the quality of the new algorithm in terms of localization and CPU time consumption.
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This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria

This paper proposes a new sensor placement approach for leak location in water distribution networks (WDNs). The sensor placement problem is formulated as an integer optimization problem. The optimization criterion consists in minimizing the number of non-isolable leaks according to the isolability criteria introduced. Because of the large size and non-linear integer nature of the resulting optimization problem, genetic algorithms (GAs) are used as the solution approach. The obtained results are compared with a semi-exhaustive search method with higher computational effort, proving that GA allows one to find near-optimal solutions with less computational load. Moreover, three ways of increasing the robustness of the GA-based sensor placement method have been proposed using a time horizon analysis, a distance-based scoring and considering different leaks sizes. A great advantage of the proposed methodology is that it does not depend on the isolation method chosen by the user, as long as it is based on leak sensitivity analysis. Experiments in two networks allow us to evaluate the performance of the proposed approach.
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Due to the characteristics of underwater acoustic channel, media access control (MAC) protocols designed for underwater acoustic sensor networks (UWASNs) are quite different from those for terrestrial wireless sensor networks. Moreover, in a sink-oriented network with event information generation in a sensor field

Due to the characteristics of underwater acoustic channel, media access control (MAC) protocols designed for underwater acoustic sensor networks (UWASNs) are quite different from those for terrestrial wireless sensor networks. Moreover, in a sink-oriented network with event information generation in a sensor field and message forwarding to the sink hop-by-hop, the sensors near the sink have to transmit more packets than those far from the sink, and then a funneling effect occurs, which leads to packet congestion, collisions and losses, especially in UWASNs with long propagation delays. An improved CDMA-based MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC), is proposed for UWASNs in this paper. In the proposed MAC protocol, both the round-robin method and CDMA technology are adopted to make the sink receive packets from multiple paths simultaneously. Since the number of paths for information gathering is much less than that of nodes, the length of the spreading code used in the POCA-CDMA-MAC protocol is shorter greatly than that used in the CDMA-based protocols with transmitter-oriented code assignment (TOCA) or receiver-oriented code assignment (ROCA). Simulation results show that the proposed POCA-CDMA-MAC protocol achieves a higher network throughput and a lower end-to-end delay compared to other CDMA-based MAC protocols.
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Vehicular communication platforms that provide real-time access to wireless networks have drawn more and more attention in recent years. IEEE 802.11p is the main radio access technology that supports communication for high mobility terminals, however, due to its limited coverage, IEEE 802.11p is

Vehicular communication platforms that provide real-time access to wireless networks have drawn more and more attention in recent years. IEEE 802.11p is the main radio access technology that supports communication for high mobility terminals, however, due to its limited coverage, IEEE 802.11p is usually deployed by coupling with cellular networks to achieve seamless mobility. In a heterogeneous cellular/802.11p network, vehicular communication is characterized by its short time span in association with a wireless local area network (WLAN). Moreover, for the media access control (MAC) scheme used for WLAN, the network throughput dramatically decreases with increasing user quantity. In response to these compelling problems, we propose a reinforcement sensor (RFS) embedded vertical handoff control strategy to support mobility management. The RFS has online learning capability and can provide optimal handoff decisions in an adaptive fashion without prior knowledge. The algorithm integrates considerations including vehicular mobility, traffic load, handoff latency, and network status. Simulation results verify that the proposed algorithm can adaptively adjust the handoff strategy, allowing users to stay connected to the best network. Furthermore, the algorithm can ensure that RSUs are adequate, thereby guaranteeing a high quality user experience.
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This paper presents a new scheme to improve the performance of finger-vein identification systems. Firstly, a vein pattern extraction method to extract the finger-vein shape and orientation features is proposed. Secondly, to accommodate the potential local and global variations at the same time,

This paper presents a new scheme to improve the performance of finger-vein identification systems. Firstly, a vein pattern extraction method to extract the finger-vein shape and orientation features is proposed. Secondly, to accommodate the potential local and global variations at the same time, a region-based matching scheme is investigated by employing the Scale Invariant Feature Transform (SIFT) matching method. Finally, the finger-vein shape, orientation and SIFT features are combined to further enhance the performance. The experimental results on databases of 426 and 170 fingers demonstrate the consistent superiority of the proposed approach.
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We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card,

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG).
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Every day we receive lots of information through our senses that is lost forever, because it lacked the strength or the repetition needed to generate a lasting memory. Combining the emerging Internet of Things and lifelogging sensors, we believe it is possible to

Every day we receive lots of information through our senses that is lost forever, because it lacked the strength or the repetition needed to generate a lasting memory. Combining the emerging Internet of Things and lifelogging sensors, we believe it is possible to build up a Digital Memory (Dig-Mem) in order to complement the fallible memory of people. This work shows how to realize the Dig-Mem in terms of interactions, affinities, activities, goals and protocols. We also complement this Dig-Mem with memory-aware services and a Dig-Mem browser. Furthermore, we propose a RFID Tag-Sharing technique to speed up the adoption of Dig-Mem. Experimentation reveals an improvement of the user understanding of Dig-Mem as time passes, compared to natural memories where the level of detail decreases over time.
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This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It

This paper deals with the attitude estimation of a rigid body equipped with angular velocity sensors and reference vector sensors. A quaternion-based nonlinear observer is proposed in order to fuse all information sources and to obtain an accurate estimation of the attitude. It is shown that the observer error dynamics can be separated into two passive subsystems connected in “feedback”. Then, this property is used to show that the error dynamics is input-to-state stable when the measurement disturbance is seen as an input and the error as the state. These results allow one to affirm that the observer is “robustly stable”. The proposed observer is evaluated in real-time with the design and implementation of an Attitude and Heading Reference System (AHRS) based on low-cost MEMS (Micro-Electro-Mechanical Systems) Inertial Measure Unit (IMU) and magnetic sensors and a 16-bit microcontroller. The resulting estimates are compared with a high precision motion system to demonstrate its performance.
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The gas-sensing properties of Pt-decorated carbon nanotubes (CNTs), which provide a foundation for the fabrication of sensors, have been evaluated. In this study, we calculated the gas adsorption of Pt-decorated (8,0) single-wall CNTs (Pt-SWCNTs) with SO2, H2S, and CO

The gas-sensing properties of Pt-decorated carbon nanotubes (CNTs), which provide a foundation for the fabrication of sensors, have been evaluated. In this study, we calculated the gas adsorption of Pt-decorated (8,0) single-wall CNTs (Pt-SWCNTs) with SO2, H2S, and CO using GGA/PW91 method based on density functional theory. The adsorption energies and the changes in geometric and electronic structures after absorption were comprehensively analyzed to estimate the responses of Pt-SWCNTs. Results indicated that Pt-SWCNTs can respond to the three gases. The electrical characteristics of Pt-SWCNTs show different changes after adsorption. Pt-SWCNTs donate electrons and increase the number of hole carriers after adsorbing SO2, thereby enhancing its conductivity. When H2S is adsorbed on CNTs, electrons are transferred from H2S to Pt-SWCNTs, converting Pt-SWCNTs from p-type to n-type sensors with improved conductivity. However, Pt-SWCNTs obtain electrons and show decreased conductivity when reacted with CO gas.
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We formulate a multi-matrices factorization model (MMF) for the missing sensor data estimation problem. The estimation problem is adequately transformed into a matrix completion one. With MMF, an n-by-t real matrix, R, is adopted to represent the data collected by mobile sensors from

We formulate a multi-matrices factorization model (MMF) for the missing sensor data estimation problem. The estimation problem is adequately transformed into a matrix completion one. With MMF, an n-by-t real matrix, R, is adopted to represent the data collected by mobile sensors from n areas at the time, T1, T2, ... , Tt, where the entry, Rij, is the aggregate value of the data collected in the ith area at Tj . We propose to approximate R by seeking a family of d-by-n probabilistic spatial feature matrices, U(1), U(2), ... , U(t), and a probabilistic temporal feature matrix, V E Rdxt, where Rj ≈ UT(j)Tj. We also present a solution algorithm to the proposed model. We evaluate MMF with synthetic data and a real-world sensor dataset extensively. Experimental results demonstrate that our approach outperforms the state-of-the-art comparison algorithms.
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Sulfur hexafluoride (SF6) gas decomposition results from the energy produced by partial discharge (PD). The detection of SO2 and H2S content, as important characteristic components of the decomposition products, is significant in the determination of the insulation level

Sulfur hexafluoride (SF6) gas decomposition results from the energy produced by partial discharge (PD). The detection of SO2 and H2S content, as important characteristic components of the decomposition products, is significant in the determination of the insulation level of SF6 gas and the inside insulation faults of gas-insulated equipment. A number of gas sensors use carbon nanotubes (CNTs). However, the applications of these sensors are limited by their low intrinsic sensitivity. In this paper, an adsorbent-mixed carbon nanotube gas sensor is proposed to improve the detection of SO2 and H2S concentrations. The sensitivity of adsorbent-mixed carbon nanotube gas sensors to SO2 and H2S at 100 ppm was investigated experimentally. The effect of the mixing ratio on the gas sensitivity characteristic and mechanism of response was also studied. The results show that compared with intrinsic CNTs gas sensors, the gas sensor featuring adsorbent-mixed CNTs has significantly higher sensitivity and responsiveness to SO2 and H2S. The resistance-change rate of SO2 and H2S increased to 33.7% and 50.9% from 0.96% and 12.9%, respectively. Moreover, the resistance-change rate and gas concentration satisfy a linear relationship. The sensor has good repeatability and stability.
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In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal

In natural and urban canyon environments, Global Navigation Satellite System (GNSS) signals suffer from various challenges such as signal multipath, limited or lack of signal availability and poor geometry. Inertial sensors are often employed to improve the solution continuity under poor GNSS signal quality and availability conditions. Various fault detection schemes have been proposed in the literature to detect and remove biased GNSS measurements to obtain a more reliable navigation solution. However, many of these methods are found to be sub-optimal and often lead to unavailability of reliability measures, mostly because of the improper characterization of the measurement errors. A robust filtering architecture is thus proposed which assumes a heavy-tailed distribution for the measurement errors. Moreover, the proposed filter is capable of adapting to the changing GNSS signal conditions such as when moving from open sky conditions to deep canyons. Results obtained by processing data collected in various GNSS challenged environments show that the proposed scheme provides a robust navigation solution without having to excessively reject usable measurements. The tests reported herein show improvements of nearly 15% and 80% for position accuracy and reliability, respectively, when applying the above approach.
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Klebsiella pneumoniae is one of the most common Gram-negative bacterial pathogens in clinical practice. It is associated with a wide range of disorders, ranging from superficial skin and soft tissue infections to potentially fatal sepsis in the lungs and blood stream. Quorum sensing,

Klebsiella pneumoniae is one of the most common Gram-negative bacterial pathogens in clinical practice. It is associated with a wide range of disorders, ranging from superficial skin and soft tissue infections to potentially fatal sepsis in the lungs and blood stream. Quorum sensing, or bacterial cell-cell communication, refers to population density-dependent gene expression modulation. Quorum sensing in Proteobacteria relies on the production and sensing of signaling molecules which are mostly N-acylhomoserine lactones. Here, we report the identification of a multidrug resistant clinical isolate, K. pneumoniae strain CSG20, using matrix-assisted laser desorption ionization-time-of-flight (MALDI-TOF) mass spectrometry. We further confirmed quorum sensing activity in this strain with the use of high resolution tandem liquid chromatography quadrupole mass spectrometry and provided evidence K. pneumoniae strain CSG20 produced N-hexanoyl-homoserine lactone (C6-HSL). To the best of our knowledge, this is the first report on the production of N-hexanoylhomoserine lactone (C6-HSL) in clinical isolate K. pneumoniae.
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This paper reports a novel coaxial cable Fabry-Perot interferometer for sensing applications. The sensor is fabricated by drilling two holes half-way into a coaxial cable. The device physics was described. The temperature and strain responses of the sensor were tested. The measurement error

This paper reports a novel coaxial cable Fabry-Perot interferometer for sensing applications. The sensor is fabricated by drilling two holes half-way into a coaxial cable. The device physics was described. The temperature and strain responses of the sensor were tested. The measurement error was calculated and analyzed.
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Fiber-optic sensors provide remote access, are readily embedded within structures, and can operate in harsh environments. Nevertheless, fiber-optic sensing of liquids has been largely restricted to measurements of refractive index and absorption spectroscopy. The temporal dynamics of fluid evaporation have potential applications in

Fiber-optic sensors provide remote access, are readily embedded within structures, and can operate in harsh environments. Nevertheless, fiber-optic sensing of liquids has been largely restricted to measurements of refractive index and absorption spectroscopy. The temporal dynamics of fluid evaporation have potential applications in monitoring the quality of water, identification of fuel dilutions, mobile point-of-care diagnostics, climatography and more. In this work, the fiber-optic monitoring of fluids evaporation is proposed and demonstrated. Sub-nano-liter volumes of a liquid are applied to inline fiber-optic micro-cavities. As the liquid evaporates, light is refracted out of the cavity at the receding index boundary between the fluid and the ambient surroundings. A sharp transient attenuation in the transmission of light through the cavity, by as much as 50 dB and on a sub-second time scale, is observed. Numerical models for the transmission dynamics in terms of ray-tracing and wavefront propagation are provided. Experiments show that the temporal transmission profile can distinguish between different liquids.
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The paper presents a multifunctional joint sensor with measurement adaptability for biological engineering applications, such as gait analysis, gesture recognition, etc. The adaptability is embodied in both static and dynamic environment measurements, both of body pose and in motion capture. Its multifunctional

The paper presents a multifunctional joint sensor with measurement adaptability for biological engineering applications, such as gait analysis, gesture recognition, etc. The adaptability is embodied in both static and dynamic environment measurements, both of body pose and in motion capture. Its multifunctional capabilities lay in its ability of simultaneous measurement of multiple degrees of freedom (MDOF) with a single sensor to reduce system complexity. The basic working mode enables 2DOF spatial angle measurement over big ranges and stands out for its applications on different joints of different individuals without recalibration. The optional advanced working mode enables an additional DOF measurement for various applications. By employing corrugated tube as the main body, the sensor is also characterized as flexible and wearable with less restraints. MDOF variations are converted to linear displacements of the sensing elements. The simple reconstruction algorithm and small outputs volume are capable of providing real-time angles and long-term monitoring. The performance assessment of the built prototype is promising enough to indicate the feasibility of the sensor.
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The vibration of a violin bridge is a dynamic contact vibration with two interfaces: strings-bridge, and bridge feet-top plate. In this paper, the mobility of an isolated bridge under in-plane excitation is explored using finite element modeling based on the contact vibration model.

The vibration of a violin bridge is a dynamic contact vibration with two interfaces: strings-bridge, and bridge feet-top plate. In this paper, the mobility of an isolated bridge under in-plane excitation is explored using finite element modeling based on the contact vibration model. Numerical results show that the dynamic contact stiffness in the two contact interfaces has a great impact on the bridge mobility. A main resonance peak is observed in the frequency range of 2–3 kHz in the frequency response of the isolated bridge when the contact stiffness is smaller than a critical threshold. The main resonance peak frequency is affected by the contact stiffness as well. In order to verify the numerical findings, a novel experimental system is then designed on the basis of a piezoelectric dynamometer for bridge mobility analysis. Experimental results confirm the impact of the dynamic contact stiffness on the bridge mobility.
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Low-cost GPS receivers provide geodetic positioning information using the NMEA protocol, usually with eight digits for latitude and nine digits for longitude. When these geodetic coordinates are converted into Cartesian coordinates, the positions fit in a quantization grid of some decimeters in size,

Low-cost GPS receivers provide geodetic positioning information using the NMEA protocol, usually with eight digits for latitude and nine digits for longitude. When these geodetic coordinates are converted into Cartesian coordinates, the positions fit in a quantization grid of some decimeters in size, the dimensions of which vary depending on the point of the terrestrial surface. The aim of this study is to reduce the quantization errors of some low-cost GPS receivers by using a Kalman filter. Kinematic tractor model equations were employed to particularize the filter, which was tuned by applying Monte Carlo techniques to eighteen straight trajectories, to select the covariance matrices that produced the lowest Root Mean Square Error in these trajectories. Filter performance was tested by using straight tractor paths, which were either simulated or real trajectories acquired by a GPS receiver. The results show that the filter can reduce the quantization error in distance by around 43%. Moreover, it reduces the standard deviation of the heading by 75%. Data suggest that the proposed filter can satisfactorily preprocess the low-cost GPS receiver data when used in an assistance guidance GPS system for tractors. It could also be useful to smooth tractor GPS trajectories that are sharpened when the tractor moves over rough terrain.
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Surface plasmon resonance (SPR) is a well-established optical biosensor technology with many proven applications in the study of molecular interactions as well as in surface and material science. SPR is usually applied in the label-free mode which may be advantageous in cases where

Surface plasmon resonance (SPR) is a well-established optical biosensor technology with many proven applications in the study of molecular interactions as well as in surface and material science. SPR is usually applied in the label-free mode which may be advantageous in cases where the presence of a label may potentially interfere with the studied interactions per se. However, the fundamental challenges of label-free SPR in terms of limited sensitivity and specificity are well known. Here we present a new concept called label-enhanced SPR, which is based on utilizing strongly absorbing dye molecules in combination with the evaluation of the full shape of the SPR curve, whereby the sensitivity as well as the specificity of SPR is significantly improved. The performance of the new label-enhanced SPR method was demonstrated by two simple model assays: a small molecule assay and a DNA hybridization assay. The small molecule assay was used to demonstrate the sensitivity enhancement of the method, and how competitive assays can be used for relative affinity determination. The DNA assay was used to demonstrate the selectivity of the assay, and the capabilities in eliminating noise from bulk liquid composition variations.
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Future wireless communications are heading towards an all-Internet Protocol (all-IP) design, and will rely on the Session Initiation Protocol (SIP) to manage services, such as voice over IP (VoIP). The centralized architecture of traditional SIP has numerous disadvantages for mobile ad hoc services

Future wireless communications are heading towards an all-Internet Protocol (all-IP) design, and will rely on the Session Initiation Protocol (SIP) to manage services, such as voice over IP (VoIP). The centralized architecture of traditional SIP has numerous disadvantages for mobile ad hoc services that may be possibly overcome by advanced peer-to-peer (P2P) technologies initially developed for the Internet. In the context of mobile sensing, P2PSIP protocols facilitate decentralized and fast communications with sensor-enabled terminals. Nevertheless, in order to make P2PSIP protocols feasible in mobile sensing networks, it is necessary to minimize overhead transmissions for signaling purposes, which reduces the battery lifetime. In this paper, we present a solution to improve the management of wireless overlay networks by defining an adaptive algorithm for the calculation of refresh time. The main advantage of the proposed algorithm is that it takes into account new parameters, such as the delay between nodes, and provides satisfactory performance and reliability levels at a much lower management overhead than previous approaches. The proposed solution can be applied to many structured P2P overlays or P2PSIP protocols. We evaluate it with Kademlia-based distributed hash tables (DHT) and dSIP.
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Due to its efficiency, reliability and better channel and resource utilization, cooperative transmission technologies have been attractive options in underwater as well as terrestrial sensor networks. Their performance can be further improved if merged with forward error correction (FEC) techniques. In this paper,

Due to its efficiency, reliability and better channel and resource utilization, cooperative transmission technologies have been attractive options in underwater as well as terrestrial sensor networks. Their performance can be further improved if merged with forward error correction (FEC) techniques. In this paper, we propose and analyze a retransmission protocol named Cooperative-Hybrid Automatic Repeat reQuest (C-HARQ) for underwater acoustic sensor networks, which exploits both the reliability of cooperative ARQ (CARQ) and the efficiency of incremental redundancy-hybrid ARQ (IR-HARQ) using rate-compatible punctured convolution (RCPC) codes. Extensive Monte Carlo simulations are performed to investigate the performance of the protocol, in terms of both throughput and energy efficiency. The results clearly reveal the enhancement in performance achieved by the C-HARQ protocol, which outperforms both CARQ and conventional stop and wait ARQ (S&W ARQ). Further, using computer simulations, optimum values of various network parameters are estimated so as to extract the best performance out of the C-HARQ protocol.
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This paper introduces a compact optical information storage sensing system. Applications of this system include longitudinal surface plasmon resonance detection of gold nanorods with a single femtosecond laser in three-dimensional space as well as data storage. A diffractive optical element (DOE) is applied

This paper introduces a compact optical information storage sensing system. Applications of this system include longitudinal surface plasmon resonance detection of gold nanorods with a single femtosecond laser in three-dimensional space as well as data storage. A diffractive optical element (DOE) is applied in the system to separate the recording-reading beam from the servo beam. This allows us to apply a single laser and one objective lens in a single optical path for the servo beam and the recording-reading beam. The optical system has a linear region of 8 λ, which is compatible with current DVD servo modules. The wavefront error of the optical system is below 0.03 λrms. The minimum grating period of the DOE is 13.4 µm, and the depth of the DOE is 1.2 µm, which makes fabrication of it possible. The DOE is also designed to conveniently control the layer-selection process, as there is a linear correlation between the displacement of the DOE and the layer-selection distance. The displacement of DOE is in the range of 0–6.045 mm when the thickness of the layer-selection is 0.3 mm. Experiments were performed and the results have been verified.
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The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically

The analysis of human behavior patterns is increasingly used for several research fields. The individualized modeling of behavior using classical techniques requires too much time and resources to be effective. A possible solution would be the use of pattern recognition techniques to automatically infer models to allow experts to understand individual behavior. However, traditional pattern recognition algorithms infer models that are not readily understood by human experts. This limits the capacity to benefit from the inferred models. Process mining technologies can infer models as workflows, specifically designed to be understood by experts, enabling them to detect specific behavior patterns in users. In this paper, the eMotiva process mining algorithms are presented. These algorithms filter, infer and visualize workflows. The workflows are inferred from the samples produced by an indoor location system that stores the location of a resident in a nursing home. The visualization tool is able to compare and highlight behavior patterns in order to facilitate expert understanding of human behavior. This tool was tested with nine real users that were monitored for a 25-week period. The results achieved suggest that the behavior of users is continuously evolving and changing and that this change can be measured, allowing for behavioral change detection.
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A simultaneous strain and temperature measurement method using a Fabry-Perot laser diode (FP-LD) and a dual-stage fiber Bragg grating (FBG) optical demultiplexer was applied to a distributed sensor system based on Brillouin optical time domain reflectometry (BOTDR). By using a Kalman filter, we

A simultaneous strain and temperature measurement method using a Fabry-Perot laser diode (FP-LD) and a dual-stage fiber Bragg grating (FBG) optical demultiplexer was applied to a distributed sensor system based on Brillouin optical time domain reflectometry (BOTDR). By using a Kalman filter, we improved the performance of the FP-LD based OTDR, and decreased the noise using the dual-stage FBG optical demultiplexer. Applying the two developed components to the BOTDR system and using a temperature compensating algorithm, we successfully demonstrated the simultaneous measurement of strain and temperature distributions under various experimental conditions. The observed errors in the temperature and strain measured using the developed sensing system were 0.6 °C and 50 με, and the spatial resolution was 1 m, respectively.
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In this work, an analysis of the transmission of ultrasonic signals generated by piezoelectric sensors for air applications is presented. Based on this analysis, an ultrasonic response model is obtained for its application to the recognition of objects and structured environments for navigation

In this work, an analysis of the transmission of ultrasonic signals generated by piezoelectric sensors for air applications is presented. Based on this analysis, an ultrasonic response model is obtained for its application to the recognition of objects and structured environments for navigation by autonomous mobile robots. This model enables the analysis of the ultrasonic response that is generated using a pair of sensors in transmitter-receiver configuration using the pulse-echo technique. This is very interesting for recognizing surfaces that simultaneously generate a multiple echo response. This model takes into account the effect of the radiation pattern, the resonant frequency of the sensor, the number of cycles of the excitation pulse, the dynamics of the sensor and the attenuation with distance in the medium. This model has been developed, programmed and verified through a battery of experimental tests. Using this model a new procedure for obtaining accurate time of flight is proposed. This new method is compared with traditional ones, such as threshold or correlation, to highlight its advantages and drawbacks. Finally the advantages of this method are demonstrated for calculating multiple times of flight when the echo is formed by several overlapping echoes.
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The outrigger truss system is one of the most frequently used lateral load resisting structural systems. However, little research has been reported on the effect of installation of outrigger trusses on improvement of lateral stiffness of a high-rise building through full-scale measurements. In

The outrigger truss system is one of the most frequently used lateral load resisting structural systems. However, little research has been reported on the effect of installation of outrigger trusses on improvement of lateral stiffness of a high-rise building through full-scale measurements. In this paper, stiffness changes of a high-rise building due to installation of outrigger trusses have been evaluated by measuring lateral displacements using a global positioning system (GPS). To confirm the error range of the GPS measurement system used in the full-scale measurement tests, the GPS displacement monitoring system is investigated through a free vibration test of the experimental model. Then, for the evaluation of lateral stiffness of a high-rise building under construction, the GPS displacement monitoring system is applied to measurements of lateral displacements of a 66-story high-rise building before and after installation of outrigger truss. The stiffness improvement of the building before and after the installation is confirmed through the changes of the natural frequencies and the ratios of the base shear forces to the roof displacements.
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To accurately detect deformation and extend the component life beyond the original design limits, structural safety monitoring techniques have attracted considerable attention in the power and process industries for decades. In this paper an on-line monitoring system for high temperature pipes in a

To accurately detect deformation and extend the component life beyond the original design limits, structural safety monitoring techniques have attracted considerable attention in the power and process industries for decades. In this paper an on-line monitoring system for high temperature pipes in a power plant is developed. The extension-based sensing devices are amounted on straight pipes, T-Joints and elbows of a main steam pipeline. During on-site monitoring for more than two years, most of the sensors worked reliably and steadily. However, the direct strain gauge could not work for long periods because of the high temperature environment. Moreover, it is found that the installation and connection of the extensometers can have a significant influence on the measurement results. The on-line monitoring system has a good alarming function which is demonstrated by detecting a steam leakage of the header.
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A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF) that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.
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Electronic noses have the benefit of obtaining smell information in a simple and objective manner, therefore, many applications have been developed for broad analysis areas such as food, drinks, cosmetics, medicine, and agriculture. However, measurement values from electronic noses have a tendency to

Electronic noses have the benefit of obtaining smell information in a simple and objective manner, therefore, many applications have been developed for broad analysis areas such as food, drinks, cosmetics, medicine, and agriculture. However, measurement values from electronic noses have a tendency to vary under humidity or alcohol exposure conditions, since several types of sensors in the devices are affected by such variables. Consequently, we show three techniques for reducing the variation of sensor values: (1) using a trapping system to reduce the infering components; (2) performing statistical standardization (calculation of z-score); and (3) selecting suitable sensors. With these techniques, we discriminated the volatiles of four types of fresh mushrooms: golden needle (Flammulina velutipes), white mushroom (Agaricus bisporus), shiitake (Lentinus edodes), and eryngii (Pleurotus eryngii) among six fresh mushrooms (hen of the woods (Grifola frondosa), shimeji (Hypsizygus marmoreus) plus the above mushrooms). Additionally, we succeeded in discrimination of white mushroom, only comparing with artificial mushroom flavors, such as champignon flavor and truffle flavor. In conclusion, our techniques will expand the options to reduce variations in sensor values.
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In this paper, a multimodal user-emotion detection system for social robots is presented. This system is intended to be used during human–robot interaction, and it is integrated as part of the overall interaction system of the robot: the Robotics Dialog System (RDS). Two

In this paper, a multimodal user-emotion detection system for social robots is presented. This system is intended to be used during human–robot interaction, and it is integrated as part of the overall interaction system of the robot: the Robotics Dialog System (RDS). Two modes are used to detect emotions: the voice and face expression analysis. In order to analyze the voice of the user, a new component has been developed: Gender and Emotion Voice Analysis (GEVA), which is written using the Chuck language. For emotion detection in facial expressions, the system, Gender and Emotion Facial Analysis (GEFA), has been also developed. This last system integrates two third-party solutions: Sophisticated High-speed Object Recognition Engine (SHORE) and Computer Expression Recognition Toolbox (CERT). Once these new components (GEVA and GEFA) give their results, a decision rule is applied in order to combine the information given by both of them. The result of this rule, the detected emotion, is integrated into the dialog system through communicative acts. Hence, each communicative act gives, among other things, the detected emotion of the user to the RDS so it can adapt its strategy in order to get a greater satisfaction degree during the human–robot dialog. Each of the new components, GEVA and GEFA, can also be used individually. Moreover, they are integrated with the robotic control platform ROS (Robot Operating System). Several experiments with real users were performed to determine the accuracy of each component and to set the final decision rule. The results obtained from applying this decision rule in these experiments show a high success rate in automatic user emotion recognition, improving the results given by the two information channels (audio and visual) separately.
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Measurement and diagnostic systems based on electronic sensors have been increasingly essential in the standardization of hospital equipment. The technical standard IEC (International Electrotechnical Commission) 60601-2-19 establishes requirements for neonatal incubators and specifies the calibration procedure and validation tests for such devices using

Measurement and diagnostic systems based on electronic sensors have been increasingly essential in the standardization of hospital equipment. The technical standard IEC (International Electrotechnical Commission) 60601-2-19 establishes requirements for neonatal incubators and specifies the calibration procedure and validation tests for such devices using sensors systems. This paper proposes a new procedure based on an inferential neural network to evaluate and calibrate a neonatal incubator. The proposal presents significant advantages over the standard calibration process, i.e., the number of sensors is drastically reduced, and it runs with the incubator under operation. Since the sensors used in the new calibration process are already installed in the commercial incubator, no additional hardware is necessary; and the calibration necessity can be diagnosed in real time without the presence of technical professionals in the neonatal intensive care unit (NICU). Experimental tests involving the aforementioned calibration system are carried out in a commercial incubator in order to validate the proposal.
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The temperature of the flue-gas in the post combustion zone of a waste to energy (WTE) plant has to be maintained within a fairly narrow range of values, the minimum of which is prescribed by the European Waste Directive 2000/76/CE, whereas the maximum

The temperature of the flue-gas in the post combustion zone of a waste to energy (WTE) plant has to be maintained within a fairly narrow range of values, the minimum of which is prescribed by the European Waste Directive 2000/76/CE, whereas the maximum value must be such as to ensure the preservation of the materials and the energy efficiency of the plant. A high degree of accuracy in measuring and controlling the aforementioned temperature is therefore required. In almost the totality of WTE plants this measurement process is carried out by using practical industrial thermometers, such as bare thermocouples and infrared radiation (IR) pyrometers, even if affected by different physical contributions which can make the gas temperature measurements incorrect. The objective of this paper is to analyze errors and uncertainties that can arise when using a bare thermocouple or an IR pyrometer in a WTE plant and to provide a method for the in situ calibration of these industrial sensors through the use of suction pyrometers. The paper describes principle of operation, design, and uncertainty contributions of suction pyrometers, it also provides the best estimation of the flue-gas temperature in the post combustion zone of a WTE plant and the estimation of its expanded uncertainty.
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Shipboard is not an absolute rigid body. Many factors could cause deformations which lead to large errors of mounted devices, especially for the navigation systems. Such errors should be estimated and compensated effectively, or they will severely reduce the navigation accuracy of the

Shipboard is not an absolute rigid body. Many factors could cause deformations which lead to large errors of mounted devices, especially for the navigation systems. Such errors should be estimated and compensated effectively, or they will severely reduce the navigation accuracy of the ship. In order to estimate the deformation, an unscented particle filter method for estimation of shipboard deformation based on an inertial measurement unit is presented. In this method, a nonlinear shipboard deformation model is built. Simulations demonstrated the accuracy reduction due to deformation. Then an attitude plus angular rate match mode is proposed as a frame to estimate the shipboard deformation using inertial measurement units. In this frame, for the nonlinearity of the system model, an unscented particle filter method is proposed to estimate and compensate the deformation angles. Simulations show that the proposed method gives accurate and rapid deformation estimations, which can increase navigation accuracy after compensation of deformation.
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Fresh jujube (Ziziphus jujube) is rich in vitamin C, which is an important quality index and generally decreases with storage time. The aim of this study was to build kinetic models for determining the vitamin C content, thus predicting the quality

Fresh jujube (Ziziphus jujube) is rich in vitamin C, which is an important quality index and generally decreases with storage time. The aim of this study was to build kinetic models for determining the vitamin C content, thus predicting the quality characteristics and shelf life of fresh jujube. The quality changes of the jujube stored at room temperature (20 °C) were analyzed using near-infrared spectroscopy. The significant spectra were determined and a calibration model for vitamin C content was developed. The results showed that vitamin C content could be described by the zero-order kinetics model based on the regressions. In addition, the shelf life of the jujube at room temperature was calculated according to the regression model.
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The Sustainable TEchnologies for LittoraLAquaculture and MArine REsearch (STELLA MARE) platform has as an objective to provide data for the management of the sea in relation with the fishing industry. In this paper, we introduce

The Sustainable TEchnologies for LittoraLAquaculture and MArine REsearch (STELLA MARE) platform has as an objective to provide data for the management of the sea in relation with the fishing industry. In this paper, we introduce the first experiment on the active tracking of a crab species, Maja squinado, symbolic of the deregulation of fishing activity. This paper introduces the method used for monitoring Maja squinado and the first collected data on the behavior of this little-known species.
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The question whether barometric altimeters can be applied to accurately track human motions is still debated, since their measurement performance are rather poor due to either coarse resolution or drifting behavior problems. As a step toward accurate short-time tracking of changes in height

The question whether barometric altimeters can be applied to accurately track human motions is still debated, since their measurement performance are rather poor due to either coarse resolution or drifting behavior problems. As a step toward accurate short-time tracking of changes in height (up to few minutes), we develop a stochastic model that attempts to capture some statistical properties of the barometric altimeter noise. The barometric altimeter noise is decomposed in three components with different physical origin and properties: a deterministic time-varying mean, mainly correlated with global environment changes, and a first-order Gauss-Markov (GM) random process, mainly accounting for short-term, local environment changes, the effects of which are prominent, respectively, for long-time and short-time motion tracking; an uncorrelated random process, mainly due to wideband electronic noise, including quantization noise. Autoregressive-moving average (ARMA) system identification techniques are used to capture the correlation structure of the piecewise stationary GM component, and to estimate its standard deviation, together with the standard deviation of the uncorrelated component.M-point moving average filters used alone or in combination with whitening filters learnt from ARMA model parameters are further tested in few dynamic motion experiments and discussed for their capability of short-time tracking small-amplitude, low-frequency motions.
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Precise Point Positioning (PPP) has become a very hot topic in GNSS research and applications. However, it usually takes about several tens of minutes in order to obtain positions with better than 10 cm accuracy. This prevents PPP from being widely used in

Precise Point Positioning (PPP) has become a very hot topic in GNSS research and applications. However, it usually takes about several tens of minutes in order to obtain positions with better than 10 cm accuracy. This prevents PPP from being widely used in real-time kinematic positioning services, therefore, a large effort has been made to tackle the convergence problem. One of the recent approaches is the ionospheric delay constrained precise point positioning (IC-PPP) that uses the spatial and temporal characteristics of ionospheric delays and also delays from an a priori model. In this paper, the impact of the quality of ionospheric models on the convergence of IC-PPP is evaluated using the IGS global ionospheric map (GIM) updated every two hours and a regional satellite-specific correction model. Furthermore, the effect of the receiver differential code bias (DCB) is investigated by comparing the convergence time for IC-PPP with and without estimation of the DCB parameter. From the result of processing a large amount of data, on the one hand, the quality of the a priori ionosphere delays plays a very important role in IC-PPP convergence. Generally, regional dense GNSS networks can provide more precise ionosphere delays than GIM and can consequently reduce the convergence time. On the other hand, ignoring the receiver DCB may considerably extend its convergence, and the larger the DCB, the longer the convergence time. Estimating receiver DCB in IC-PPP is a proper way to overcome this problem. Therefore, current IC-PPP should be enhanced by estimating receiver DCB and employing regional satellite-specific ionospheric correction models in order to speed up its convergence for more practical applications.
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The condition of locomotive bearings, which are essential components in trains, is crucial to train safety. The Doppler effect significantly distorts acoustic signals during high movement speeds, substantially increasing the difficulty of monitoring locomotive bearings online. In this study, a new Doppler transient

The condition of locomotive bearings, which are essential components in trains, is crucial to train safety. The Doppler effect significantly distorts acoustic signals during high movement speeds, substantially increasing the difficulty of monitoring locomotive bearings online. In this study, a new Doppler transient model based on the acoustic theory and the Laplace wavelet is presented for the identification of fault-related impact intervals embedded in acoustic signals. An envelope spectrum correlation assessment is conducted between the transient model and the real fault signal in the frequency domain to optimize the model parameters. The proposed method can identify the parameters used for simulated transients (periods in simulated transients) from acoustic signals. Thus, localized bearing faults can be detected successfully based on identified parameters, particularly period intervals. The performance of the proposed method is tested on a simulated signal suffering from the Doppler effect. Besides, the proposed method is used to analyze real acoustic signals of locomotive bearings with inner race and outer race faults, respectively. The results confirm that the periods between the transients, which represent locomotive bearing fault characteristics, can be detected successfully.
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During the manufacturing of printed electronic circuits, different layers of coatings are applied successively on a substrate. The correct thickness of such layers is essential for guaranteeing the electronic behavior of the final product and must therefore be controlled thoroughly. This paper presents

During the manufacturing of printed electronic circuits, different layers of coatings are applied successively on a substrate. The correct thickness of such layers is essential for guaranteeing the electronic behavior of the final product and must therefore be controlled thoroughly. This paper presents a model for measuring two-layer systems through thin film reflectometry (TFR). The model considers irregular interfaces and distortions introduced by the setup and the vertical vibration movements caused by the production process. The results show that the introduction of these latter variables is indispensable to obtain correct thickness values. The proposed approach is applied to a typical configuration of polymer electronics on transparent and non-transparent substrates. We compare our results to those obtained using a profilometer. The high degree of agreement between both measurements validates the model and suggests that the proposed measurement method can be used in industrial applications requiring fast and non-contact inspection of two-layer systems. Moreover, this approach can be used for other kinds of materials with known optical parameters.
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A novel zinc porphyrin-containing polyimide (ZPCPI) nanofibrous membrane for rapid and reversible detection of trace amounts of pyridine vapor is described. The membrane displays a distinct color change, as well as dramatic variations in absorption and fluorescent emission spectra, upon exposure to pyridine

A novel zinc porphyrin-containing polyimide (ZPCPI) nanofibrous membrane for rapid and reversible detection of trace amounts of pyridine vapor is described. The membrane displays a distinct color change, as well as dramatic variations in absorption and fluorescent emission spectra, upon exposure to pyridine vapor. This condition allows the detection of the analyte at concentrations as low as 0.041 ppm. The vapochromic and spectrophotometric responses of the membrane are attributed to the formation of the ZPCPI-pyridine complex upon axial coordination. From surface plasmon resonance analysis, the affinity constant of ZPCPI-pyridine complex was calculated to be (3.98 ± 0.25) × 104 L·mol−1. The ZPCPI nanofibrous membrane also showed excellent selectivity for pyridine vapor over other common amines, confirming its applicability in the manufacture of pyridine-sensitive gas sensors.
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To investigate the drive-mode resonance frequency of a micromachined vibratory gyroscope (MVG), one needs to measure it accurately and efficiently. The conventional approach to measure the resonant frequency is by performing a sweep frequency test and spectrum analysis. The method is time-consuming and

To investigate the drive-mode resonance frequency of a micromachined vibratory gyroscope (MVG), one needs to measure it accurately and efficiently. The conventional approach to measure the resonant frequency is by performing a sweep frequency test and spectrum analysis. The method is time-consuming and inconvenient because of the requirements of many test points, a lot of data storage and off-line analyses. In this paper, we propose two novel measurement methods, the search method and track method, respectively. The former is based on the magnitude-frequency characteristics of the drive mode, utilizing a one-dimensional search technique. The latter is based on the phase-frequency characteristics, applying a feedback control loop. Their performances in precision, noise resistivity and efficiency are analyzed through detailed simulations. A test system is implemented based on a field programmable gate array (FPGA) and experiments are carried out. By comparing with the common approach, feasibility and superiorities of the proposed methods are validated. In particular, significant efficiency improvements are achieved whereby the conventional frequency method consumes nearly 5,000 s to finish a measurement, while only 5 s is needed for the track method and 1 s for the search method.
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The micromechanical silicon resonant accelerometer has attracted considerable attention in the research and development of high-precision MEMS accelerometers because of its output of quasi-digital signals, high sensitivity, high resolution, wide dynamic range, anti-interference capacity and good stability. Because of the mismatching thermal expansion

The micromechanical silicon resonant accelerometer has attracted considerable attention in the research and development of high-precision MEMS accelerometers because of its output of quasi-digital signals, high sensitivity, high resolution, wide dynamic range, anti-interference capacity and good stability. Because of the mismatching thermal expansion coefficients of silicon and glass, the micromechanical silicon resonant accelerometer based on the Silicon on Glass (SOG) technique is deeply affected by the temperature during the fabrication, packaging and use processes. The thermal stress caused by temperature changes directly affects the frequency output of the accelerometer. Based on the working principle of the micromechanical resonant accelerometer, a special accelerometer structure that reduces the temperature influence on the accelerometer is designed. The accelerometer can greatly reduce the thermal stress caused by high temperatures in the process of fabrication and packaging. Currently, the closed-loop drive circuit is devised based on a phase-locked loop. The unloaded resonant frequencies of the prototype of the micromechanical silicon resonant accelerometer are approximately 31.4 kHz and 31.5 kHz. The scale factor is 66.24003 Hz/g. The scale factor stability is 14.886 ppm, the scale factor repeatability is 23 ppm, the bias stability is 23 μg, the bias repeatability is 170 μg, and the bias temperature coefficient is 0.0734 Hz/°C.
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In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from

In this paper we present a complete spike-based architecture: from a Dynamic Vision Sensor (retina) to a stereo head robotic platform. The aim of this research is to reproduce intended movements performed by humans taking into account as many features as possible from the biological point of view. This paper fills the gap between current spike silicon sensors and robotic actuators by applying a spike processing strategy to the data flows in real time. The architecture is divided into layers: the retina, visual information processing, the trajectory generator layer which uses a neuroinspired algorithm (SVITE) that can be replicated into as many times as DoF the robot has; and finally the actuation layer to supply the spikes to the robot (using PFM). All the layers do their tasks in a spike-processing mode, and they communicate each other through the neuro-inspired AER protocol. The open-loop controller is implemented on FPGA using AER interfaces developed by RTC Lab. Experimental results reveal the viability of this spike-based controller. Two main advantages are: low hardware resources (2% of a Xilinx Spartan 6) and power requirements (3.4 W) to control a robot with a high number of DoF (up to 100 for a Xilinx Spartan 6). It also evidences the suitable use of AER as a communication protocol between processing and actuation.
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High infrared absorption, large temperature coefficient of resistance (TCR) and small 1/f noise are preferred characteristics for sensing materials used in bolometers. In this paper, we discuss a cytochrome c protein as a potential sensing material for long-wavelength bolometers. We simulated and experimentally

High infrared absorption, large temperature coefficient of resistance (TCR) and small 1/f noise are preferred characteristics for sensing materials used in bolometers. In this paper, we discuss a cytochrome c protein as a potential sensing material for long-wavelength bolometers. We simulated and experimentally proved high infrared absorption of cytochrome c in the wavelength between 8 μm and 14 μm. Cytochrome c thin films were deposited on a hydrophilic surface using the spin coating method. The resistance variation with temperature is measured and we show that the TCR of cytochrome c thin films is consistently higher than 20%. The measured values of 1/f noise were as low as 2.33 × 10–13 V2/Hz at 60 Hz. Finally, we test the reliability of cytochrome c by measuring the resistance changes over time under varying conditions. We found that cytochrome c thin films deteriorated significantly without appropriate packaging.
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Spirometry is regarded as the only effective method for detecting pulmonary function test (PFT) indices. In this study, a novel impedance pulmonary function measurement system (IPFS) is developed for directly assessing PFT indices. IPFS can obtain high resolution values and remove motion artifacts

Spirometry is regarded as the only effective method for detecting pulmonary function test (PFT) indices. In this study, a novel impedance pulmonary function measurement system (IPFS) is developed for directly assessing PFT indices. IPFS can obtain high resolution values and remove motion artifacts through real-time base impedance feedback. Feedback enables the detection of PFT indices using only both hands for convenience. IPFS showed no differences in the sitting, supine, and standing postures during the measurements, indicating that patient posture has no effect on IPFS. Mean distance analysis showed good agreement between the volume and flow signal of IPFS (p < 0.05). PFT indices were detected in subjects to differentiate a chronic obstructive pulmonary disease (COPD) patient group from a normal group. The forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), FEV1/FVC, and peak expiratory flow (PEF) in the COPD group were lower than those in the normal group by IPFS (p < 0.05). IPFS is therefore suitable for evaluating pulmonary function in normal and COPD patients. Moreover, IPFS could be useful for periodic monitoring of existing patients diagnosed with obstructive lung disease.
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Electronic Olfaction Systems (EOSs) based on a variety of gas-sensing technologies have been developed to simulate in a simplified manner animal olfactory sensing systems. EOSs have been successfully applied to many applications and fields, including food technology and agriculture. Less information is available

Electronic Olfaction Systems (EOSs) based on a variety of gas-sensing technologies have been developed to simulate in a simplified manner animal olfactory sensing systems. EOSs have been successfully applied to many applications and fields, including food technology and agriculture. Less information is available for EOS applications in the feed technology and animal nutrition sectors. Volatile Organic Compounds (VOCs), which are derived from both forages and concentrate ingredients of farm animal rations, are considered and described in this review as olfactory markers for feedstock quality and safety evaluation. EOS applications to detect VOCs from feedstuffs (as analytical matrices) are described, and some future scenarios are hypothesised. Furthermore, some EOS applications in animal feeding behaviour and organoleptic feed assessment are also described.
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Synthesis—particularly by electrochemical anodization-, growth mechanism and chemical sensing properties of pure, doped and mixed titania tubular arrays are reviewed. The first part deals on how anodization parameters affect the size, shape and morphology of titania nanotubes. In the second part fabrication of

Synthesis—particularly by electrochemical anodization-, growth mechanism and chemical sensing properties of pure, doped and mixed titania tubular arrays are reviewed. The first part deals on how anodization parameters affect the size, shape and morphology of titania nanotubes. In the second part fabrication of sensing devices based on titania nanotubes is presented, together with their most notable gas sensing performances. Doping largely improves conductivity and enhances gas sensing performances of TiO2 nanotubes
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Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling)

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals.
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Algal blooms are a frequent phenomenon in nearly all kinds of fresh water. Global warming and eutrophication by waste water, air pollution and fertilizers seem to lead to an increased frequency of occurrence. Many cyanobacteria produce hazardous and quite persistent toxins, which can

Algal blooms are a frequent phenomenon in nearly all kinds of fresh water. Global warming and eutrophication by waste water, air pollution and fertilizers seem to lead to an increased frequency of occurrence. Many cyanobacteria produce hazardous and quite persistent toxins, which can contaminate the respective water bodies. This may limit the use of the raw water for many purposes. The purification of the contaminated water might be quite costly, which makes a continuous and large scale treatment economically unfeasible in many cases. Due to the obvious risks of algal toxins, an online or mobile detection method would be highly desirable. Several biosensor systems have been presented in the literature for this purpose. In this review, their mode of operation, performance and general suitability for the intended purpose will be described and critically discussed. Finally, an outlook on current developments and future prospects will be given.
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Aptamer-based bioreceptors that can easily adopt their surroundings have captured the attention of scientists from a wide spectrum of domains in designing highly sensitive, selective and structure switchable sensing assays. Through elaborate design and chemical functionalization, numerous aptamer-based assays have been developed that

Aptamer-based bioreceptors that can easily adopt their surroundings have captured the attention of scientists from a wide spectrum of domains in designing highly sensitive, selective and structure switchable sensing assays. Through elaborate design and chemical functionalization, numerous aptamer-based assays have been developed that can switch their conformation upon incubation with target analyte, resulting in an enhanced output signal. To further lower the detection limits to picomolar levels, nanomaterials have attracted great interest in the design of aptamer-based sensing platforms. Associated to their unique properties, nanomaterials offer great promise for numerous aptasensing applications. This review will discuss current research activities in the aptasensing with typical example of detection of ochratoxin A (OTA). OTA, a secondary fungal metabolite, contaminates a variety of food commodities, and has several toxicological effects such as nephrotoxic, hepatotoxic, neurotoxic, teratogenic and immunotoxic activities. The review will introduce advances made in the methods of integrating nanomaterials in aptasensing, and will discuss current conformational switchable design strategies in aptasensor fabrication methodologies.
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Temperatures of hot section components in today’s gas turbine engines reach as high as 1,500 °C, making in situ monitoring of the severe temperature gradients within the engine rather difficult. Therefore, there is a need to develop instrumentation (i.e., thermocouples and

Temperatures of hot section components in today’s gas turbine engines reach as high as 1,500 °C, making in situ monitoring of the severe temperature gradients within the engine rather difficult. Therefore, there is a need to develop instrumentation (i.e., thermocouples and strain gauges) for these turbine engines that can survive these harsh environments. Refractory metal and ceramic thin film thermocouples are well suited for this task since they have excellent chemical and electrical stability at high temperatures in oxidizing atmospheres, they are compatible with thermal barrier coatings commonly employed in today’s engines, they have greater sensitivity than conventional wire thermocouples, and they are non-invasive to combustion aerodynamics in the engine. Thin film thermocouples based on platinum:palladium and indium oxynitride:indium tin oxynitride as well as their oxide counterparts have been developed for this purpose and have proven to be more stable than conventional type-S and type-K thin film thermocouples. The metallic and ceramic thin film thermocouples described within this paper exhibited remarkable stability and drift rates similar to bulk (wire) thermocouples.
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Redox processes are involved in almost every cell of the body as a consequence of aerobic life. In the past decades, redox biology has been increasingly recognized as one of the key themes in cell signaling. The progress has been accelerated by development

Redox processes are involved in almost every cell of the body as a consequence of aerobic life. In the past decades, redox biology has been increasingly recognized as one of the key themes in cell signaling. The progress has been accelerated by development of fluorescent probes that can monitor redox conditions and dynamics in cells and cell compartments. This short paper focuses on fluorescent redox probes that are genetically encoded, and discusses their properties, molecular mechanism, advantages and pitfalls. Our recent work on reaction-based encoded probes that are responsive to particular redox signaling molecules is also reviewed. Future challenges and directions are also commented.
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The Internet of Things (IoT) is a networking paradigm where interconnected, smart objects continuously generate data and transmit it over the Internet. Much of the IoT initiatives are geared towards manufacturing low-cost and energy-efficient hardware for these objects, as well as the communication

The Internet of Things (IoT) is a networking paradigm where interconnected, smart objects continuously generate data and transmit it over the Internet. Much of the IoT initiatives are geared towards manufacturing low-cost and energy-efficient hardware for these objects, as well as the communication technologies that provide objects interconnectivity. However, the solutions to manage and utilize the massive volume of data produced by these objects are yet to mature. Traditional database management solutions fall short in satisfying the sophisticated application needs of an IoT network that has a truly global-scale. Current solutions for IoT data management address partial aspects of the IoT environment with special focus on sensor networks. In this paper, we survey the data management solutions that are proposed for IoT or subsystems of the IoT. We highlight the distinctive design primitives that we believe should be addressed in an IoT data management solution, and discuss how they are approached by the proposed solutions. We finally propose a data management framework for IoT that takes into consideration the discussed design elements and acts as a seed to a comprehensive IoT data management solution. The framework we propose adapts a federated, data- and sources-centric approach to link the diverse Things with their abundance of data to the potential applications and services that are envisioned for IoT.
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In [1], we would like to change “Gate” to “Gait” in the title, which should read “Prototype Based on Pressure and Bending Sensors for Measuring Gait Quality”. In Figure 7 we would like to change the analog inputs. The measurements should be between

In [1], we would like to change “Gate” to “Gait” in the title, which should read “Prototype Based on Pressure and Bending Sensors for Measuring Gait Quality”. In Figure 7 we would like to change the analog inputs. The measurements should be between the sensor and the resistance, and not after the resistance. The revised figure is shown below. [...]
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